Triple
T19404912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taguspark campus |
E485427
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Oeiras |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Oeiras | Statement: [Taguspark campus, locatedIn, Oeiras]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oeiras Context triple: [Taguspark campus, locatedIn, Oeiras]
-
A.
Oeiras
chosen
Oeiras is a coastal municipality in the Lisbon metropolitan area of Portugal, known for its residential suburbs, business parks, and proximity to the capital.
-
B.
Oeiras
Oeiras is a historic city in the Brazilian state of Piauí, known for being the state's first capital and for its well-preserved colonial architecture.
-
C.
Odivelas
Odivelas is a suburban city and municipality in the Lisbon metropolitan area of Portugal, known for its residential character and proximity to the capital.
-
D.
Vila do Conde
Vila do Conde is a coastal city in northern Portugal known for its historic shipbuilding heritage, beaches, and well-preserved medieval architecture.
-
E.
Barreiro
Barreiro is a Portuguese city located on the south bank of the Tagus River opposite Lisbon, known historically for its industrial activity and as a commuter hub for the capital.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6257a361c8190bf019fc350faa225 |
completed | April 20, 2026, 1:09 p.m. |
Created at: April 10, 2026, 1:36 p.m.